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The cost to train machine learning models has been increasing exponentially, making exploration and research into the correct features and architecture a costly or intractable endeavor at scale.
Trueskill™: a bayesian skill rating system
Ralf Herbrich, Tom Minka, and Thore Graepel · 2007
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Earlier work this paper cites.
bitfield: Python fast integer set implementation
Steve Stagg · 2013
Earlier work this paper cites.
Net2net: Accelerating learning via knowledge transfer
Tianqi Chen, Ian Goodfellow, and Jonathon Shlens · 2015
Earlier work this paper cites.
Understanding intermediate layers using linear classifier probes
Guillaume Alain and Yoshua Bengio · 2016
Cited alongside, same era.
Densecap: Fully convolutional localization networks for dense captioning
Justin Johnson, Andrej Karpathy, and Li Fei-Fei · 2016
Cited alongside, same era.
AI and compute
Dario Amodei and Danny Hernandez · 2018
Cited alongside, same era.
Multilingual constituency parsing with self-attention and pre-training
Nikita Kitaev and Dan Klein · 2018
Cited alongside, same era.
Tensorflow: A system for large-scale machine learning
Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al
Cited in the paper.
Deeptype: multilingual entity linking by neural type system evolution
Jonathan Raphael Raiman and Olivier Michel Raiman · 2018
Later among the works it cites.
Openai Five
OpenAI · 2018
Later among the works it cites.
Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
Closest in time.
Playing Dota 2 with Large Scale Deep Reinforcement Learning, 2019
OpenAI · 2019
Closest in time.
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